from decoder_mc import v_mainchain, show_mutiply_structures,get_sidechain_angles,get_1d_mc_sd


from  mc_sc_to_residues  import lst_residue,c_pdb
import pickle

#file_path = 

# large numbers samples genreations

import torch
import pickle
name_f = "iter64_64_large_number"

def g_pdb(pkl_name):
    with open(pkl_name,"rb") as f:
        d1= pickle.load(f)
    a = torch.zeros([d1.shape[0],14,42])
    for i in range(len(d1)):
        a[i,:14,:42] = d1[i,0,:14,:42]
    g_data = a
    for i in range(len(g_data)):

        data = g_data[i].detach().numpy()

        seq, mc, sd = get_1d_mc_sd(data)
        seq_lst.append(seq)
        c_pdb(seq,mc,sd,"tmp/test_file"+name_f+str(i)+"_Cov2_h1024.pdb")




